JOURNAL ARTICLE

Efficient quantization scheme for lattice-reduction aided MIMO detection

Abstract

In this paper, we present an efficient quantization scheme for lattice-reduction (LR) aided (LRA) MIMO detection using Gram-Schmidt orthogonalization. For the LRA detection, the quantization step applies the simple rounding operation, which often leads to the quantization errors. Meanwhile, these errors may result in the detection errors. Hence, the motivation of the proposed detection is to further solve the problem of degrading the performance due to the quantization errors in the signal estimation. In this paper, the proposed quantization scheme decreases the quantization errors using a simple tree search with a threshold function. Through the analysis and the simulation results, the proposed detection can achieve the near-ML performance with only a little additional complexity.

Keywords:
Quantization (signal processing) Rounding Orthogonalization Algorithm Linde–Buzo–Gray algorithm MIMO Computer science Mathematics Telecommunications

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Topics

Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Wireless Communication Techniques
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Blind Source Separation Techniques
Physical Sciences →  Computer Science →  Signal Processing

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Lattice-reduction-aided MIMO detection

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JOURNAL ARTICLE

An Improved Quantization Scheme for Lattice-Reduction Aided MIMO Detection Based on Gram-Schmidt Orthogonalization

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